Academy for Engineering & Technology, Fudan University, Shanghai, China.
Intelligent Robot Engineering Research Center of Ministry of Education, Shanghai Intelligent Robot Engineering Technology Research Center, Shanghai, China.
Int J Med Robot. 2024 Aug;20(4):e2667. doi: 10.1002/rcs.2667.
Robot-assisted microsurgery (RAMS) is gradually becoming the preferred method for some delicate surgical procedures. However, the lack of haptic feedback reduces the safety of the surgery. Surgeons are unable to feel the grasping force between surgical instruments and the patient's tissues, which can easily lead to grasping failure or tissue damage.
This paper proposes a tendon-driven grasping force feedback mechanism, consisting of a follower hand and a leader hand, to address the lack of grasping force feedback in flexible surgical robots. Considering the friction in the tendon transmission process, a grasping force estimation model is established for the follower hand. The admittance control model is designed for force/position control of the leader hand.
Through experimental validation, it has been confirmed that the grasping force sensing range of the follower hand is 0.5-5 N, with a sensing accuracy of 0.3 N. The leader hand is capable of providing feedback forces in the range of 0-5 N, with a static force accuracy of 0.1 N.
The designed mechanism and control strategy can provide the grasping force feedback function. Future work will focus on improving force feedback performance.
This research has no clinical trials.
机器人辅助微创手术(RAMS)逐渐成为一些精细手术的首选方法。然而,缺乏触觉反馈降低了手术的安全性。外科医生无法感受到手术器械和患者组织之间的抓取力,这容易导致抓取失败或组织损伤。
本文提出了一种腱驱动的抓取力反馈机构,由从动手和主动手组成,以解决柔性手术机器人中缺乏抓取力反馈的问题。考虑到腱传动过程中的摩擦,建立了从动手的抓取力估计模型。设计了导入手的导纳控制模型,用于力/位置控制。
通过实验验证,确认了从动手的抓取力感应范围为 0.5-5 N,感应精度为 0.3 N。导入手能够提供 0-5 N 的反馈力,静态力精度为 0.1 N。
设计的机构和控制策略可以提供抓取力反馈功能。未来的工作将重点提高力反馈性能。
本研究没有临床试验。